{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T09:33:12Z","timestamp":1772184792247,"version":"3.50.1"},"reference-count":31,"publisher":"Georg Thieme Verlag KG","issue":"02","license":[{"start":{"date-parts":[[2017,12,21]],"date-time":"2017-12-21T00:00:00Z","timestamp":1513814400000},"content-version":"vor","delay-in-days":264,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"Mike Becich","award":["UL1TR001857\u201301"],"award-info":[{"award-number":["UL1TR001857\u201301"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2017,4]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>Background: Patient matching is a key barrier to achieving interoperability. Patient demographic elements must be consistently collected over time and region to be valuable elements for patient matching.<\/jats:p><jats:p>Objectives: We sought to determine what patient demographic attributes are collected at multiple institutions in the United States and see how their availability changes over time and across clinical sites.<\/jats:p><jats:p>Methods: We compiled a list of 36 demographic elements that stakeholders previously identified as essential patient demographic attributes that should be collected for the purpose of linking patient records. We studied a convenience sample of 9 health care systems from geographically distinct sites around the country. We identified changes in the availability of individual patient demographic attributes over time and across clinical sites.<\/jats:p><jats:p>Results: Several attributes were consistently available over the study period (2005\u20132014) including last name (99.96%), first name (99.95%), date of birth (98.82%), gender\/sex (99.73%), postal code (94.71%), and full street address (94.65%). Other attributes changed significantly from 2005\u20132014: Social security number (SSN) availability declined from 83.3% to 50.44% (p&lt;0.0001). Email address availability increased from 8.94% up to 54% availability (p&lt;0.0001). Work phone number increased from 20.61% to 52.33% (p&lt;0.0001).<\/jats:p><jats:p>Conclusions: Overall, first name, last name, date of birth, gender\/sex and address were widely collected across institutional sites and over time. Availability of emerging attributes such as email and phone numbers are increasing while SSN use is declining. Understanding the relative availability of patient attributes can inform strategies for optimal matching in healthcare.<\/jats:p><jats:p>Citation: Culbertson A, Goel S, Madden MB, Jackson KL, Carton T, Waitman R, Liu M, Krishnamurthy A, Hall L, Cappella N, Visweswaran S, Safaeinili N, Becich MJ, Applegate R, Bernstam E, Rothman R, Matheny M, Lipori G, Bian J, Hogan W, Bell D, Martin A, Grannis S, Klann J, Sutphen R, O\u2019Hara AB, Kho A. The building blocks of interoperability: A multisite analysis of patient demographic attributes available for matching. Appl Clin Inform 2017; 8: 322\u2013336 https:\/\/doi.org\/10.4338\/ACI-2016-11-RA-0196<\/jats:p>","DOI":"10.4338\/aci-2016-11-ra-0196","type":"journal-article","created":{"date-parts":[[2017,4,5]],"date-time":"2017-04-05T02:57:32Z","timestamp":1491361052000},"page":"322-336","source":"Crossref","is-referenced-by-count":17,"title":["The Building Blocks of Inter-operability"],"prefix":"10.4338","volume":"08","author":[{"given":"Adam","family":"Culbertson","sequence":"additional","affiliation":[]},{"given":"Satyender","family":"Goel","sequence":"additional","affiliation":[]},{"given":"Margaret","family":"Madden","sequence":"additional","affiliation":[]},{"given":"Niloufar","family":"Safaeinili","sequence":"additional","affiliation":[]},{"given":"Kathryn","family":"Jackson","sequence":"additional","affiliation":[]},{"given":"Thomas","family":"Carton","sequence":"additional","affiliation":[]},{"given":"Russ","family":"Waitman","sequence":"additional","affiliation":[]},{"given":"Mei","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ashok","family":"Krishnamurthy","sequence":"additional","affiliation":[]},{"given":"Lauren","family":"Hall","sequence":"additional","affiliation":[]},{"given":"Nickie","family":"Cappella","sequence":"additional","affiliation":[]},{"given":"Shyam","family":"Visweswaran","sequence":"additional","affiliation":[]},{"given":"Michael","family":"Becich","sequence":"additional","affiliation":[]},{"given":"Reuben","family":"Applegate","sequence":"additional","affiliation":[]},{"given":"Elmer","family":"Bernstam","sequence":"additional","affiliation":[]},{"given":"Russell","family":"Rothman","sequence":"additional","affiliation":[]},{"given":"Michael","family":"Matheny","sequence":"additional","affiliation":[]},{"given":"Gloria","family":"Lipori","sequence":"additional","affiliation":[]},{"given":"Jiang","family":"Bian","sequence":"additional","affiliation":[]},{"given":"William","family":"Hogan","sequence":"additional","affiliation":[]},{"given":"Douglas","family":"Bell","sequence":"additional","affiliation":[]},{"given":"Andrew","family":"Martin","sequence":"additional","affiliation":[]},{"given":"Shaun","family":"Grannis","sequence":"additional","affiliation":[]},{"given":"Jeff","family":"Klann","sequence":"additional","affiliation":[]},{"given":"Rebecca","family":"Sutphen","sequence":"additional","affiliation":[]},{"given":"Amy","family":"O\u2019Hara","sequence":"additional","affiliation":[]},{"given":"Abel","family":"Kho","sequence":"additional","affiliation":[]}],"member":"194","published-online":{"date-parts":[[2017,12,21]]},"reference":[{"key":"10.4338\/ACI-2016-11-RA-0196-1","unstructured":"Where Is HITECH\u2019s $35 Billion Dollar Investment Going? 2016. 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